The effect of individual differences on thermal stress response for semi-nude supine human subjects in transient environments is modeled using an experimental data set. Two transient climatic parameters and seven individual characteristics are used as inputs to predict three thermal responses using a novel transient computational model. The model is developed using a neural network after ensuring generalization and also checking with results reported in the literature for predictions. It reliably predicts core temperature, skin temperature, and heart rate in transient environmental conditions for individual subjects. A methodology is then proposed to identify the relative importance of the individual parameters and of environmental conditions on thermal stress using a sensitivity analysis. The results have applications for heat stress monitoring and other biomedical applications.

Units: SI